The Kinouchi-Copelli model[1]} proposed in 2006 gives a concrete realization that a network of excitable elements maximizes its sensitivity (and thus dynamic range) at the critical point of a non-equilibrium phase transition. In the Article, we adopt a square-lattice network composed of the 4-state Kinouchi-Copelli neurons to analyze the information processing. The internal states of a Kinouchi-Copelli neuron is labeled by \(s = 0,1,\cdots , n-1\)  with \(n=4\)  here. The state \(s=0\)  represents the resting state and the state \(s=1\)  corresponds to the excited state. The other states \(s=2, 3\)  are refractory and are insensitive to stimulus.
